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Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey
INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalenc...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The African Field Epidemiology Network
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992900/ https://www.ncbi.nlm.nih.gov/pubmed/33796165 http://dx.doi.org/10.11604/pamj.2020.37.351.21167 |
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author | Mwangi, Kibachio Joseph Mwenda, Valerian Gathecha, Gladwell Beran, David Guessous, Idris Ombiro, Oren Ndegwa, Zachary Masibo, Peninnah |
author_facet | Mwangi, Kibachio Joseph Mwenda, Valerian Gathecha, Gladwell Beran, David Guessous, Idris Ombiro, Oren Ndegwa, Zachary Masibo, Peninnah |
author_sort | Mwangi, Kibachio Joseph |
collection | PubMed |
description | INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata. RESULTS: tobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis. CONCLUSION: prevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya. |
format | Online Article Text |
id | pubmed-7992900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The African Field Epidemiology Network |
record_format | MEDLINE/PubMed |
spelling | pubmed-79929002021-03-31 Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey Mwangi, Kibachio Joseph Mwenda, Valerian Gathecha, Gladwell Beran, David Guessous, Idris Ombiro, Oren Ndegwa, Zachary Masibo, Peninnah Pan Afr Med J Research INTRODUCTION: non-communicable diseases (NCDs) are projected to become the leading cause of death in Africa by 2030. Gender and socio-economic differences influence the prevalence of NCDs and their risk factors. METHODS: we performed a secondary analysis of the STEPS 2015 data to determine prevalence and correlation between diabetes, hypertension, harmful alcohol use, smoking, obesity and injuries across age, gender, residence and socio-economic strata. RESULTS: tobacco use prevalence was 13.5% (males 19.9%, females 0.9%, p<0.001); harmful alcohol use was 12.6% (males 18.1%, females 2.2%, p<0.001); central obesity was 27.9% (females 49.5%, males 32.9%, p=0.017); type 2 diabetes prevalence 3.1% (males 2.0%, females 2.8%, p=0.048); elevated blood pressure prevalence was 23.8% (males 25.1%, females 22.6%, p<0.001), non-use of helmets 72.8% (males 89.5%, females 56.0%, p=0.031) and seat belts non-use 67.9% (males 79.8%, females 56.0%, p=0.027). Respondents with <12 years of formal education had higher prevalence of non-use of helmets (81.7% versus 54.1%, p=0.03) and seat belts (73.0% versus 53.9%, p=0.039). Respondents in the highest wealth quintile had higher prevalence of type II diabetes compared with those in the lowest (5.2% versus 1.6%,p=0.008). Rural dwellers had 35% less odds of tobacco use (aOR 0.65, 95% CI 0.49, 0.86) compared with urban dwellers, those with ≥12 years of formal education had 89% less odds of tobacco use (aOR 0.11, 95% CI 0.07, 0.17) compared with <12 years, and those belonging to the wealthiest quintile had 64% higher odds of unhealthy diets (aOR 1.64, 95% CI 1.26, 2.14). Only 44% of respondents with type II diabetes and 16% with hypertension were aware of their diagnosis. CONCLUSION: prevalence of NCD risk factors is high in Kenya and varies across socio-demographic attributes. Socio-demographic considerations should form part of multi-sectoral, integrated approach to reduce the NCD burden in Kenya. The African Field Epidemiology Network 2020-12-16 /pmc/articles/PMC7992900/ /pubmed/33796165 http://dx.doi.org/10.11604/pamj.2020.37.351.21167 Text en Copyright: Kibachio Joseph Mwangi et al. https://creativecommons.org/licenses/by/4.0 The Pan African Medical Journal (ISSN: 1937-8688). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Mwangi, Kibachio Joseph Mwenda, Valerian Gathecha, Gladwell Beran, David Guessous, Idris Ombiro, Oren Ndegwa, Zachary Masibo, Peninnah Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey |
title | Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey |
title_full | Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey |
title_fullStr | Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey |
title_full_unstemmed | Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey |
title_short | Socio-economic and demographic determinants of non-communicable diseases in Kenya: a secondary analysis of the Kenya stepwise survey |
title_sort | socio-economic and demographic determinants of non-communicable diseases in kenya: a secondary analysis of the kenya stepwise survey |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7992900/ https://www.ncbi.nlm.nih.gov/pubmed/33796165 http://dx.doi.org/10.11604/pamj.2020.37.351.21167 |
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